Conventional video searching and editing typically involves searching through individual frames of a video sequence to find a specific frame or frames. For example, a video from a parking lot surveillance camera may record many hours of footage, but only frames showing a particular car leaving its parking space may be desirable. Using conventional editing techniques, a user may have to search sequentially through the entire video to find the time when the car leaves its parking space. Brute force searching of this nature can be time consuming and inefficient. Further, the desired footage may not exist within the video.